Pricing strategies and advance payment-based inventory model with partially backlogged shortages under interval uncertainty. Issue 1 (31st December 2023)

• Record Type: Journal Article
• Authors: Mondal, Rajan; Das, Subhajit; Das, Subhash Chandra; Shaikh, Ali Akbar; Bhunia, Asoke Kumar
• Is Part Of: International journal of systems science. Volume 10:Issue 1(2023)
• Publication Date: 2023-12-31
• Subjects: Interval-valued demand -- interval-valued deterioration -- interval-valued backlogging -- advance payment policy -- c-r optimisation technique; Operations research -- Periodicals; Logistics -- Periodicals; System analysis -- Periodicals; 003
• DOI: 10.1080/23302674.2022.2070296
• Languages: English
• ISSNs: 2330-2674

Abstract

Abstract : In the current market situation, uncertainty in the market economy plays a significant role for proper controlling of inventory. In this situation, during an analysis of an inventory system with more realistic assumptions, it becomes a necessity to consider the imprecise behaviour of various inventory parameters. This work demonstrates a partially backlogged inventory model with interval uncertainty in which products during stock-in situation deteriorate at a certain rate. Two distinct cases are considered based on the advance payment and availability of discount. In the first case, the retailer makes full payment in advance to the corresponding supplier, and for this regard, supplier offers some price discount on the total purchasing cost. In the second case, the retailer makes partial payment in advance to the supplier but no discount facility is available. However, the retailer needs to make the rest of the payment at the time of receiving a lot from the supplier. As the inventory parameters are considered interval-valued, the objective function of the corresponding optimisation problem is converted into interval-valued, and to solve the same problem, the c-r optimisation technique is used. Two numerical examples are considered and solved using three distinct variants of QPSO to check the feasibility of the proposed model.